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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- massive |
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metrics: |
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- accuracy |
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base_model: distilbert-base-uncased |
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model-index: |
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- name: distilbert-base-uncased-finetuned-massive-intent-detection-english |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: massive |
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type: massive |
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args: en-US |
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metrics: |
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- type: accuracy |
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value: 0.886684599865501 |
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name: Accuracy |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# distilbert-base-uncased-finetuned-massive-intent-detection-english |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the massive dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4873 |
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- Accuracy: 0.8867 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.5849 | 1.0 | 360 | 1.3826 | 0.7359 | |
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| 1.0662 | 2.0 | 720 | 0.7454 | 0.8357 | |
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| 0.5947 | 3.0 | 1080 | 0.5668 | 0.8642 | |
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| 0.3824 | 4.0 | 1440 | 0.5007 | 0.8770 | |
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| 0.2649 | 5.0 | 1800 | 0.4829 | 0.8824 | |
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| 0.1877 | 6.0 | 2160 | 0.4843 | 0.8824 | |
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| 0.1377 | 7.0 | 2520 | 0.4858 | 0.8834 | |
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| 0.1067 | 8.0 | 2880 | 0.4924 | 0.8864 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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